Google Google Cloud Certified ADP

ADP자격증시험은 전문적인 관련지식을 테스트하는 인증시험입니다.은 여러분이 ADP 시험을 통과할수 있도록 도와주는 사이트입니다. 많은 분들이 많은 시간과 돈을 들여 학원까지 다니면서 Google ADP시험패스에 최선을 다합니다. 하지만 ADP덤프를 구매하시면 20시간 좌우만 투자하면 무조건 ADP시험을 패스할 수 있도록 도와드립니다.

PDF , Testing Engine , Online Test Engine 세가지 버전

ADP덤프는 PDF버전 , Testing Engine버전 , Online Test Engine 버전 세가지 버전으로 되어있습니다. ADP덤프의 세가지 버전중 한가지 버전만 구매하셔도 되고 세가지 버전을 패키지로 구매하셔도 됩니다. ADP덤프의 PDF버전은 출력가능하고 Testing Engine버전은 Google ADP시험환경을 체험해보실수 있습니다. Online Test Engine 버전은 APP로서 휴대폰으로도 간편하게 사용할수 있습니다. 고객님께서 원하시는 버전을 선택하여 구매하시면 됩니다.

최신 Google Cloud Certified ADP 무료샘플문제:

1. Your organization has several datasets in their data warehouse in BigQuery. Several analyst teams in different departments use the datasets to run queries. Your organization is concerned about the variability of their monthly BigQuery costs. You need to identify a solution that creates a fixed budget for costs associated with the queries run by each department. What should you do?

A) Create a single reservation by using BigQuery editions. Assign all analysts to the reservation.
B) Assign each analyst to a separate project associated with their department. Create a single reservation for each department by using BigQuery editions. Create assignments for each project in the appropriate reservation.
C) Assign each analyst to a separate project associated with their department. Create a single reservation by using BigQuery editions. Assign all projects to the reservation.
D) Create a custom quota for each analyst in BigQuery.

2. Your company uses Looker to visualize and analyze sales dat
a. You need to create a dashboard that displays sales metrics, such as sales by region, product category, and time period. Each metric relies on its own set of attributes distributed across several tables. You need to provide users the ability to filter the data by specific sales representatives and view individual transactions. You want to follow the Google-recommended approach. What should you do?

A) Use Looker's custom visualization capabilities to create a single visualization that displays all the sales metrics with filtering and drill-down functionality.
B) Use BigQuery to create multiple materialized views, each focusing on a specific sales metric. Build the dashboard using these views.
C) Create multiple Explores, each focusing on each sales metric. Link the Explores together in a dashboard using drill-down functionality.
D) Create a single Explore with all sales metrics. Build the dashboard using this Explore.

3. You are predicting customer churn for a subscription-based service. You have a 50 PB historical customer dataset in BigQuery that includes demographics, subscription information, and engagement metrics. You want to build a churn prediction model with minimal overhead. You want to follow the Google-recommended approach. What should you do?

A) Use the BigQuery Python client library in a Jupyter notebook to query and preprocess the data in BigQuery. Use the CREATE MODEL statement in BigQueryML to train the churn prediction model.
B) Create a Looker dashboard that is connected to BigQuery. Use LookML to predict churn.
C) Use Dataproc to create a Spark cluster. Use the Spark MLlib within the cluster to build the churn prediction model.
D) Export the data from BigQuery to a local machine. Use scikit- learn in a Jupyter notebook to build the churn prediction model.

4. You are designing a BigQuery data warehouse with a team of experienced SQL developers. You need to recommend a cost- effective, fully-managed, serverless solution to build ELT processes with SQL pipelines.
Your solution must include source code control, environment parameterization, and data quality checks. What should you do?

A) Use Cloud Data Fusion to visually design and manage the pipelines.
B) Use Dataproc to run MapReduce jobs for distributed data processing.
C) Use Dataform to build, orchestrate, and monitor the pipelines.
D) Use Cloud Composer to orchestrate and run data workflows.

5. Your organization uses a BigQuery table that is partitioned by ingestion time. You need to remove data that is older than one year to reduce your organization's storage costs. You want to use the most efficient approach while minimizing cost. What should you do?

A) Require users to specify a partition filter using the alter table statement in SQL.
B) Create a scheduled query that periodically runs an update statement in SQL that sets the "deleted" column to "yes" for data that is more than one year old. Create a view that filters out rows that have been marked deleted.
C) Set the table partition expiration period to one year using the ALTER TABLE statement in SQL.
D) Create a view that filters out rows that are older than one year.

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